Download pdf - Optical Imaging Laboratory, Department of Biomedical ...sfpmed.org/wp-content/uploads/2019/02/Photo... · Photoacoustic tomography: principles and advances Jun Xia1,†, Junjie Yao1,†,

Photoacoustic tomography: principles and advances

Jun Xia1,†, Junjie Yao1,†, and Lihong V. Wang1,*

1Optical Imaging Laboratory, Department of Biomedical Engineering, Washington University in St. Louis, One Brookings Drive, St. Louis, Missouri 63130, USA

Abstract

Photoacoustic tomography (PAT) is an emerging imaging modality that shows great potential for

preclinical research and clinical practice. As a hybrid technique, PAT is based on the acoustic

detection of optical absorption from either endogenous chromophores, such as oxy-hemoglobin

and deoxy-hemoglobin, or exogenous contrast agents, such as organic dyes and nanoparticles.

Because ultrasound scatters much less than light in tissue, PAT generates high-resolution images

in both the optical ballistic and diffusive regimes. Over the past decade, the photoacoustic

technique has been evolving rapidly, leading to a variety of exciting discoveries and applications.

This review covers the basic principles of PAT and its different implementations. Strengths of

PAT are highlighted, along with the most recent imaging results.

Keywords

Photoacoustic tomography; photoacoustic microscopy; photoacoustic computed tomography; vascular imaging; anatomical imaging; functional imaging; molecular imaging; brain imaging; tumor imaging; nanoparticle; super resolution

1. INTRODUCTION

With recent advances in photonics and optical molecular probes, optical imaging plays an

increasingly important role in preclinical and clinical imaging. A fundamental constraint of

optical imaging is light diffusion, which limits the spatial resolution in deep-tissue imaging.

In the past decade, photoacoustic (PA) tomography (PAT) has emerged as a promising

modality that overcomes this challenge [1, 2]. PAT capitalizes on the photoacoustic effect,

which converts absorbed optical energy into acoustic energy. Because acoustic waves scatter

much less than optical waves in tissue, PAT can generate high-resolution images in both the

optically ballistic and diffusive regimes. With signals originating from optical absorption,

PAT readily takes advantage of rich endogenous and exogenous optical contrasts. For

instance, endogenous oxy- and deoxy-hemoglobin can serve as anatomical and functional

contrasts for imaging vascular structures, hemoglobin oxygen saturation (sO2) [3], the speed

of blood flow [4], and the metabolic rate of oxygen [5]. A broad choice of exogenous

contrasts, including dyes [6, 7], nanoparticles [8–10], and reporter genes [11, 12], can be

used for molecular imaging. In molecular PAT, molecular images are naturally co-registered

*Corresponding author: [email protected].†These authors contributed equally.

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with high-resolution anatomical/vascular images, enabling precise localization of the

molecular process. Compared with other mainstream biomedical imaging modalities, the

merits of PAT can be summarized as follows. (1) Compared with purely optical

tomography, such as diffuse optical tomography (DOT) and fluorescence tomography

(FMT), PAT can penetrate deeper and sustain high spatial resolution within the entire field

of view. (2) Compared with ultrasonic imaging, PAT has rich intrinsic and extrinsic optical

contrasts and is free of speckle artifacts. (3) Compared with X-ray computed tomography

(X-ray CT) and positron emission tomography (PET), PAT uses nonionizing laser

illumination. (4) Compared with magnetic resonance imaging (MRI), PAT is faster and less

expensive. These unique advantages position PAT to make a broad impact in preclinical

studies and clinical practice.

Over the past ten years, PAT has been evolving rapidly, and applications of PAT have been

established in vascular biology [13–16], oncology [17–24], neurology [25–29],

ophthalmology [30–34], dermatology [35–39], gastroenterology [40–44], and cardiology

[37, 45–47]. The purpose of this review is to provide a general overview of the PAT

technique. The second section covers the fundamental principles of PAT, including signal

generation and image formation. The third section introduces the two major

implementations of PAT, photoacoustic computed tomography (PACT) and photoacoustic

microscopy (PAM). The last section highlights the strengths of PAT and describes the most

recent advances.

2. PRINCIPLES OF PHOTOACOUSTIC TOMOGRAPHY

2.1. Signal generation in PAT

As mentioned previously, PAT signals originate from optical absorption. The process of

photoacoustic signal generation can be described in three steps: (1) an object absorbs light,

(2) the absorbed optical energy is converted into heat and generates a temperature rise, and

(3) thermoelastic expansion takes place, resulting in the emission of acoustic waves. Typical

endogenous tissue chromophores (optical absorbers) include hemoglobin, melanin, and

water. As shown in Figure 1, the optical absorption coefficients are sensitive to wavelength,

and thus the concentration of each chromophore can be extracted through spectroscopic

inversion. For instance, functional photoacoustic imaging of sO2 relies on the absorption

difference between oxy-hemoglobin (HbO2) and deoxy-hemoglobin (HbR) [3].

To generate acoustic waves, the thermal expansion needs to be time variant. This

requirement can be achieved by using either a pulsed laser [48] or a continuous-wave (CW)

laser with intensity modulation at a constant [49] or variable frequency [50]. Pulsed

excitations are the most widely used because they provide a higher signal to noise ratio than

CW excitations, if both use the maximum allowable fluence or power set by the American

National Standards Institute (ANSI) [49, 51, 52]. Following a short laser pulse excitation,

the local fractional volume expansion dV/V can be expressed as

(1)

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where κ is the isothermal compressibility, β is the thermal coefficient of volume expansion,

and p(r⃗) and T(r⃗) are changes in pressure and temperature, respectively.

For effective PAT signal generation, the laser pulse duration is normally within several

nanoseconds, which is less than both the thermal and stress confinement times. The thermal

confinement indicates that thermal diffusion during laser illumination can be neglected, i.e.,

[53]

(2)

Here, τth is the thermal confinement threshold, dc is the desired spatial resolution, and DT is

the thermal diffusivity (~0.14 mm2/s for soft tissue [54]).

The stress confinement means the volume expansion of the absorber during the illumination

period can be neglected. This condition can be written as

(3)

where vs is the speed of sound.

For a 100 µm spatial resolution, the thermal confinement time is 18 ms and the stress

confinement time is 67 ns. A typical pulsed laser has a pulse duration of only 10 ns. In this

case, the fractional volume expansion in Eq. (1) is negligible and the initial photoacoustic

pressure p0(r⃗) can be written as

(4)

For soft tissue, κ is approximately 5×10−10 Pa−1 and β is around 4 × 10−4 K−1. Thus each

mK temperature rise generates a 800 Pa pressure rise, which is detectable ultrasonically. The

temperature rise can be further expressed as a function of optical absorption,

(5)

Here ρ is the mass density, CV is the specific heat capacity at constant volume, and Ae is the

absorbed energy density, which is a product of the absorption coefficient μa and the local

optical fluence F(r⃗).

Based on Eqs. (4) and (5), the initial photoacoustic pressure can be written as

(6)

Here is the Grueneisen parameter, which increases as the temperature rises.

Thus PAT can also be used to monitor temperature [55, 56]. Eq. (6) indicates that, to extract

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the object’s absorption coefficient from pressure measurements, the local fluence F(r⃗) needs

to be quantified.

Once the initial pressure p0(r⃗) is generated, it splits into two waves with equal magnitude,

traveling in opposite directions. The shape of the wavefront depends on the geometry of the

object. For a spherical object, two spherical waves will be generated: one travels outward,

and the other travels inward as compression followed by rarefaction. Thus the photoacoustic

signal has a bipolar shape and the distance between the two peaks is proportional to the size

of the object. In other words, a smaller object generates a photoacoustic signal with higher

frequency components.

The generated photoacoustic pressure propagates through the sample and is detected by an

ultrasonic transducer or transducer array. The goal of photoacoustic image formation is to

recover the distribution of p0(r⃗) from the time-resolved ultrasonic signals.

2.2. Image formation in PAT

Based on the image formation methods, PAT has two major implementations [2]. The first,

direct image formation, is based on mechanical scanning of a focused single-element

ultrasonic transducer, and is commonly used in photoacoustic microscopy (PAM). The

second, reconstruction image formation, is based on mechanical/electronic scanning of a

multi-element transducer array, and is used in photoacoustic computed tomography (PACT).

In PAM, the received photoacoustic signal originates primarily from the volume laterally

confined by the acoustic focus and can be simply converted into a one-dimensional image

along the acoustic axis. In PACT, each transducer element has a large acceptance angle

within the field of view, and a PA image can only be reconstructed only by merging data

from all transducer elements. In the following, we will discuss PACT image reconstruction

in detail.

For an ideal point transducer placed at r⃗d, the detected photoacoustic signal can be written as

[57]

(7)

Here, dΩ is the solid-angle element of r⃗ with respect to the point at r⃗d, and vs is the speed of

sound. Eq. (7) indicates that the detected pressure at time t comes from sources over a

spherical shell centered at the detector position r⃗d with a radius vst. The initial pressure

distribution p0(r⃗) can be obtained by inverting Eq. (7). For spherical, planar, and cylindrical

detection geometries, exact inversion solutions have been provided by Xu et al. [57]. The

so-called universal back-projection (UBP) algorithm can be expressed in the temporal

domain as [58]:

(8)

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Here, Ω0 is the solid angle of the whole detection surface S with respect to a given source

point at r⃗. Eq. (8) indicates that p0(r⃗) can be obtained by back-projecting the filtered data,

, onto a collection of concentric spherical surfaces that are centered

at each transducer location r ⃗d, with dΩ/Ω0 as the weighting factor applied to each back-

projection.

A variety of other reconstruction algorithms have also been developed [59–61]. Among

them, the time-reversal (TR) method is the least restrictive [62], as it can be applied to

arbitrarily closed surfaces and can incorporate acoustic heterogeneities, such as variations in

speed of sound and acoustic attenuation [61, 63]. In the TR method, the measured acoustic

waves are retransmitted in a temporally reversed order. This procedure is done by solving

the wave propagation model backwards from t = T to t = 0, using the measured data as the

boundary condition. Here T is the maximum time for the wave to traverse the detection

domain. Solving such an equation requires numerical methods, such as finite-difference

techniques [64]. Compared to UBP, TR is computationally more intensive, as it needs to

compute the wavefield within the entire detection geometry. An open source MATLAB

toolbox (k-Wave) for TR reconstruction has been made available by Treeby et al.[64].

Both UBP and TR algorithms assume idealized point-like ultrasonic transducers with a large

acceptance angle and an infinite temporal-frequency bandwidth, which are practically

unachievable. The impact of transducer characteristics on spatial resolution was first

investigated by Xu et al. in 2003, who found that the bandwidth affects both axial and lateral

resolutions, while the detector aperture mainly affects the lateral resolution [65]. In terms of

reconstruction accuracy, directly applying UBP or TR algorithms to experimental data could

be problematic because the transducer response acts as an additional filter to the original

pressure. Recently, based on the transducer characteristics, advanced image reconstruction

algorithms have been developed to provide more accurate images than UBP or TR [66, 67].

It should also be noted that, in practice, the detection surface can never be infinite and can

hardly be closed. For instance, due to the chest wall, a spherical-view breast scanner can

achieve only hemi-spherical coverage. As a consequence, only part of the photoacoustic

wavefront is detected, yielding incomplete data. Such limited-view PACT normally suffers

from missing or blurred boundaries [68]. In addition, the spatial sampling over the detection

aperture could be insufficient, causing streaking artifacts or grating lobes [69]. A variety of

algorithms have been proposed to improve the image quality of limited-view or under-

sampled PACT. For instance, iterative image reconstruction algorithms have been developed

to enhance the boundary sharpness [68]. For linear-array-based PACT systems, acoustic

reflectors have been employed to redirect part of the photoacoustic wave back to the

transducer, and thus improve the detection coverage [70]. When the target objects are

sparse, compressed-sensing-based algorithms have been used in PACT to reduce the density

of spatial sampling [69, 71].

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3. PHOTOACOUSTIC TOMOGRAPHY SYSTEMS

3.1. Photoacoustic computed tomography

As mentioned above, PACT has three canonical detection geometries: planar, cylindrical,

and spherical. Each geometry has a variety of implementations. For a planar-view PACT

system, the photoacoustic signal can be detected by either a 2D matrix piezoelectric

transducer array [72] or a Fabry-Perot interferometer (FPI) (Figure 2a) [73, 74]. Ideally,

each transducer element needs to be smaller than the acoustic wavelength in order to ensure

a large receiving angle. In this regard, the FPI sensor is advantageous because of its high

detection sensitivity and small element size, which is defined by the focal size of the probe

beam. However, because the current FPI-based PACT system uses only one probe beam

(Figure 2a), its imaging speed is much lower than that of a 2D-matrix-array-based PACT

system [72]. Figure 2b shows an in situ image of the abdomen of a pregnant mouse,

acquired by the FPI-based PACT system [75]. Two embryos (shaded red) can be clearly

seen, along with the vasculature of the uterus and the skin.

Cylindrical-view PACT is commonly implemented by a ring-transducer array. To improve

the cross-sectional imaging capability, each element in the array is usually cylindrically

focused, and thus rejects out-of-plane signals. Strictly speaking, such a system is a circular-

view PACT. However, a three-dimensional (3D) image can still be acquired by scanning the

sample or array along the elevational direction. The 3D data can be reconstructed using a

modified back projection algorithm, which accounts for the transducer’s spatial response

[76]. Compared to planar- and spherical-view PACT, which can perform only 3D imaging,

circular-view PACT has both 2D and 3D imaging capabilities, and can be used for high-

speed cross-sectional (2D) dynamic imaging [77]. Figure 3 shows a schematic of a ring-

array-based small-animal imaging system and representative images [78]. Blood-rich

organs, such as the liver, spleen, spine, kidneys, and gastrointestinal (GI) tract, are clearly

visible. Detailed vascular structures within these organs are also visible, indicating that the

system can be used for angiographic imaging.

A spherical-view PACT system can provide nearly isotropic spatial resolution within the

central imaging region. There are multiple variations of spherical-view PACT, including an

arc-shaped transducer array that scans around the object [80, 81] and a hemispherical

transducer array with elements distributed in a spiral pattern [82, 83]. Both systems require

mechanical scanning, and an image can be reconstructed only after a complete 3D scan,

making real-time imaging challenging. Advanced image reconstruction algorithms, such as

highly constrained back projection [82], have been proposed to allow dynamic imaging from

highly under-sampled data. Figure 4a is a photograph of an arc-array-based spherical-view

PACT system [80]. For a complete volumetric scan, the animal was rotated 360 degrees in

150 steps. The volumetric image (Figure 4b) clearly shows the left and right kidneys, the

spleen, and a partial lobe of the liver. The inferior vena cava and its bifurcation into the

femoral veins can be seen.

For all three detection geometries, the axial resolution is spatially invariant and is primarily

determined by the bandwidth of the ultrasonic transducer [65]. For a wideband transducer,

the axial resolution, a, approximates 0.6λc, where λc is the acoustic wavelength at the high

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cutoff frequency. The lateral resolution for spherical- and cylindrical-view PACTs can be

characterized by , where r is the distance between the imaging point and the

scanning center, r0 is the radius of the scan circle, and d is the width of each transducer

element [84]. The lateral resolution for a planar-view PACT can be characterized by

.

3.2. Photoacoustic microscopy

Photoacoustic microscopy (PAM) is another major implementation of PAT, which images

targets in the (quasi)ballistic and quasidiffusive regimes at high spatial resolution at depths

[85]. Here, we define microscopy as an imaging modality with a spatial resolution finer than

50 µm, since unaided eyes can discern only features larger than 50 µm. As mentioned

previously, the most significant difference between PAM and PACT is that PAM uses a

focused single-element ultrasonic transducer for direct image formation, while PACT

typically uses a multi-element transducer array or its equivalent for digital image

reconstruction.

The lateral resolution of PAM is determined by the product of the point spread functions of

the light illumination and acoustic detection [85]. The axial resolution of PAM is determined

by the detection bandwidth of the ultrasonic transducer, which is chosen to match the

acoustic path length due to frequency-dependent acoustic attenuation in tissue [85]. Based

on the dominant determining factor for lateral resolution, PAM can be further classified into

optical-resolution PAM (OR-PAM) and acoustic-resolution PAM (AR-PAM). In OR-PAM,

the laser beam is tightly focused to a diffraction-limited spot, which is typically more than

10 times smaller in diameter than the acoustic focusing. Therefore, the lateral resolution of

OR-PAM is primarily determined by the optical focal spot size (Figure 5a) [86, 87]. Since

OR-PAM relies highly on the tight optical focusing, it can penetrate about one optical

transport mean free path (TMFT) in tissue (~1 mm in muscle and ~0.6 mm in the brain),

limited by the strong optical scattering. In contrast, in AR-PAM, the excitation laser beam is

only loosely focused to fulfill the entire acoustic detection volume (Figure 5b). In this case,

the lateral resolution does not closely depend on the tissue’s optical scattering

characteristics, because it is the ultrasonic focusing that determines the lateral resolution at

depths within a few TMFTs [3, 88]. As a variant of PAM miniaturized for internal organ

imaging, photoacoustic endoscopy (PAE) is typically based on rotational scanning [89–93].

PAE can be configured in either optical-resolution [90] or acoustic-resolution modes [93].

By adjusting the optical illumination and/or acoustic detection configurations, PAM can

scale in spatial resolution and penetration depth over a wide range [85]. Specifically, the

lateral resolution of OR-PAM can be scaled down by either increasing the numerical

aperture (NA) of the objective lens or using a shorter excitation wavelength, with the

maximum imaging depth scaled accordingly. In comparison, the lateral resolution of AR-

PAM can be scaled by varying the acoustic central frequency and the NA of the acoustic

lens. Detailed reviews about PAM technologies can be found in two recent publications [2,

85].

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4. STRENGTHS OF PAT

4.1. Multi-scale PAT

As a hybrid technique, PAT has the unique capability of scaling its spatial resolution and

imaging depth across both optical and ultrasonic dimensions [2]. For OR-PAM, whose

lateral resolution is mainly determined by the numerical aperture (NA) of the optical

microscopic objective, a higher NA improves the lateral resolution, but decreases the

imaging depth. For instance, a 1.23-NA OR-PAM system has a 0.22 µm lateral resolution

and 100 µm imaging depth, while a 0.1-NA OR-PAM system has a 2.6 µm lateral resolution

and a 1.2 mm imaging depth [2]. In the optically diffusive region, the spatial resolution is

acoustically defined. While a higher central frequency transducer provides a higher spatial

resolution, the frequency-dependent acoustic attenuation (~1 dB/MHz/cm in muscle) limits

the imaging depth. Thus an AR-PAM system normally employs a transducer with a central

frequency greater than 20 MHz to provide a sub 100 µm lateral resolution with an imaging

depth of several millimeters. Low frequency (< 10 MHz) transducers are commonly used in

PACT systems to provide an imaging depth greater than 1 cm. Above 10 cm, the imaging

depth is also limited by light attenuation, which is a combined effect of optical absorption

and scattering. With recent advances in optical wave-front engineering [95, 96], we expect

the attenuation through optical scattering to be minimized, and PAT to eventually image

tens of centimeters deep in tissue.

The multi-scale imaging capability of PAT was demonstrated by imaging the expression of

LacZ, a widely used reporter gene in molecular imaging [97]. It encodes β-galactosidase, an

E. coli enzyme responsible for metabolizing lactose into glucose and galactose. This enzyme

also causes bacteria expressing the gene to appear blue when grown on a medium that

contains the substrate analog X-gal [98]. The blue product has strong optical absorption at

wavelengths from 605 nm to 665 nm, and thus provides a good contrast for deep PA

imaging. The multi-scale PAT experiment was performed on a mouse with a subcutaneously

inoculated tumor. To demonstrate the imaging depth, multiple pieces of chicken breast

tissues were overlaid on the tumor, and photoacoustic images were acquired by a linear

ultrasound transducer array with 4 – 8 MHz bandwidth [99]. Figure 6a is a composite

photoacoustic and ultrasound B-mode image. It can be seen that the expression of LacZ

remained visible at a depth of 5 cm in biological tissue. The tumor-to-background contrast

was found to be 3 [99]. The chicken breast tissues were then removed, and the mouse was

imaged using the AR-PAM system with a 45 µm lateral resolution and a 15 µm axial

resolution. Two laser wavelengths, 635 nm and 584 nm, were used to maximize the

difference between the optical absorption of hemoglobin and the blue product. The

combined image in Figure 6b clearly shows the spatial relation between the tumor and the

surrounding microvasculature. An OR-PAM system was also used. Figure 6c shows fixed

lacZ cells grown on a cover glass after staining with X-gal. With a spatial resolution of 0.4

µm, the lacZ cell structure can be resolved. Strong absorbers can be seen around the low

absorbing center (cell nuclei), indicating that the blue product exists mostly in the

cytoplasm.

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This study demonstrates that PAT can image reporter genes from the microscopic to the

macroscopic scales. Currently multi-scale PAT imaging is performed using different PAT

systems. With the introduction of optical-resolution photoacoustic computed microscopy

[100], which achieves optical-resolution imaging in a PACT system, multi-scale PAT

images can potentially be acquired using a single setup.

4.2. Super-resolution PAT

Super-resolution imaging has opened new possibilities for fundamental biological studies.

With resolutions finer than the optical diffraction limit (~250 nm in lateral direction at high

optical NA), super-resolution imaging has enabled observations of cellular and subcellular

structures and processes that are unresolvable by conventional microscopes [101]. However,

most of the existing super-resolution imaging techniques can perform only fluorescence

imaging by using multiple lasers and/or chemical manipulation of fluorophores, resulting in

complex system configurations and strict requirements for the fluorescent targets. PAT, on

the other hand, can potentially image both fluorescent and nonfluorescent molecules at

appropriate wavelengths. Recently, progress has been made to break the diffraction limits in

PAT for super-resolution imaging.

In OR-PAM, Yao et al. overcame the optical-diffraction limit by using the excitation-

intensity dependence of the photobleaching effect (Figure 7a–b) [102]. Within the optical

focal spot, molecules in the center part of the illuminated region are bleached more than

those in the periphery, leaving an imprint in the sample. The pixel-by-pixel differences

between the image acquired before and after the bleaching highlight the central region of the

excitation spot. Sub-diffraction PA imaging of gold nanoparticles has been demonstrated

with a resolution of ~80 nm, three times smaller than the optical diffraction limit. Another

sub-optical-diffraction PA imaging method was reported by Nedosekin et al., with a

resolution of ~100 nm for nanoparticles, where nonlinear signal amplification by

nanobubbles circumvented the optical diffraction limit [103]. In this method, the center

region of the excitation spot generated nanobubbles with greater sizes than the periphery.

Collapse of the nanobubbles enhanced the PA signals non-uniformly across the excitation

field, highlighting the center region.

In addition to the sub-optical-diffraction imaging in the optical (quasi)ballistic regime in

ORPAM, sub-acoustic-diffraction imaging in the optical diffusive regime has also been

achieved in AR-PAM. Conkey et al. and Lai et al. reported sub-acoustic-diffraction imaging

methods using the photoacoustic signal as feedback for wavefront shaping optimization

[104, 105]. Conkey et al.’s method takes advantage of the Gaussian-shape detection

sensitivity of a focused ultrasonic transducer (Figure 7c–e). Photoacoustic imaging behind a

scattering medium was demonstrated with a resolution of ~13 µm, five to six times smaller

than the acoustic diffraction limit [104]. Based on the Grueneisen memory effect, Lai et al.’s

method utilizes nonlinear PA signals as feedback to guide iterative wavefront optimization

[105]. Experimental results demonstrated an optical diffraction-limited focus on the scale of

5–7 µm in scattering media, ten times smaller than the acoustic diffraction limit, with an

enhancement factor of ~6,000 in peak fluence [105].

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4.3. Multi-parameter PAT

PA signals can be used to derive a number of anatomical, functional, and metabolic

parameters of the tissue microenvironment. Since a single parameter may not be able to fully

reflect the true physiological and pathological conditions, multi-parameter PA imaging can

potentially provide more comprehensive information for diagnosis, staging, and treatment of

diseases. Here, we will review a few representative parameters that can be measured by

PAT, together with the corresponding technologies.

For hemoglobin, the total concentration (CHb) and oxygen saturation (sO2) are the most

commonly used indexes of blood perfusion and oxygenation, respectively. In particular,

increased CHb due to angiogenesis and decreased sO2 due to hypoxia are both hallmarks of

late stage cancers, while hyperoxia is associated with early-stage cancers (Figure 8) [5, 106].

From fluence-compensated PA measurements at the isosbestic wavelengths of hemoglobin

(498 nm, 568 nm, and 794 nm), the PA signal amplitude reflects the CHb distribution,

regardless of the oxygenation level [5]. From fluence-compensated PA measurements at two

or more wavelengths, the relative concentrations of the two forms of hemoglobin (HbO2 and

HbR) can be quantified through spectral analysis, and thus sO2 can be computed [5, 101,

107–112]. In practice, however, accurate laser fluence compensation for absolute CHb and

sO2 quantification can be very challenging, especially for AR-PAM and PACT. A potential

solution is to incorporate PAT with diffuse reflectance spectroscopy [113] or diffuse optical

tomography (DOT) [114], which can quantify the tissue’s optical properties or the fluence

distribution. Alternatively, the frequency spectra of PA signals at multiple optical

wavelengths can be used to fit for absolute concentrations of HbO2 and HbR, and thus CHb

and sO2, where fluence compensation is not required [115, 116]. Recently, another

calibration-free method for absolute sO2 quantification in PACT has been developed by Xia

et al., based on the dynamics of the PA signals at different oxygenation states [117].

Using the excellent absorption contrast between intra- and extra-vascular spaces provided by

hemoglobin, PAT can be employed to measure blood flow [109, 111, 118–120]. So far, a

number of methods have been developed for PA measurement of blood flow speed. Similar

to Doppler ultrasound, photoacoustic Doppler flowmetry measures the axial flow speed on

the basis of Doppler frequency shift [4, 121, 122]. Correlation-based photoacoustic

flowmetry measures the transverse or axial flow speeds by performing either temporal

autocorrelation [18, 123–126] or cross-correlation [127] over consecutive photoacoustic

waveforms, respectively. Photoacoustic thermal flowmetry can measure flow speed based

on thermal convection [128]. Similarly, PA imaging of wash-in and wash-out dynamics of

nanoparticles or organic dyes can also provide flow information [129–131]. Another

method, developed by Zhang et al., measures the flow speed in a homogenous medium,

based on structured illumination and the Doppler frequency shift induced by the flowing

medium [132]. However, all of the above methods have difficulty in deep flow

measurement, because they all rely on resolvable particles in the media or clearly defined

illumination patterns. This issue has recently been solved by thermally tagging the flowing

medium using a HIFU (high-intensity focused ultrasound) transducer and detecting the

tagged medium using AR-PAM and PACT [56, 133]. Blood flow under a 5-mm-thick layer

of chicken tissue was measured with a sensitivity of 0.25 mm/s [56].

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The metabolism of oxygen and glucose directly reflects tissue functioning. Almost all

diseases, especially cancers, manifest abnormal oxygen and glucose metabolisms [106, 134].

Currently, OR-PAM can noninvasively quantify absolute oxygen metabolism using

endogenous contrast [5, 135]. Alternatively, PAM can be integrated with Doppler OCT or

Doppler ultrasound for oxygen metabolism quantification, where PAM is used for blood

oxygenation measurement, while Doppler OCT or Doppler ultrasound quantifies blood flow

[136, 137]. Further, by integrating fine spatial and temporal scales, single-cell PA

flowoxigraphy, a new implementation of OR-PAM, is capable of imaging oxygen release

from single red blood cells (RBCs) in vivo [138].

Although glucose has been explored as an endogenous contrast agent for PAT measurement

of blood sugar levels, the detection sensitivity is still insufficient for clinical diagnosis [139].

Recently, two glucose analogs, 2-NBDG and IRDye-800-DG, have been used to

noninvasively quantify glucose metabolism in mice. Similar to the FDG used in PET, 2-

NBDG and IRDye-800-DG are transported into cells but cannot be further metabolized.

Therefore, the distribution of the trapped glucose analogs reflects the glucose uptake and

thus the local glucose metabolism. PACT with 2-NBDG and IRDye-800-2DG was used to

study mouse brain metabolism and tumor hypermetabolism, respectively [132].

In addition to the above major functional and metabolic parameters, PAT can also measure a

number of other tissue properties. Although some of these parameters can be obtained by

fluorescence imaging as well, PAT can achieve deeper penetration at high spatial resolution

than its fluorescence counterpart. PAT can also measure the temperature distribution in

thermotherapy by using the temperature dependence of the Grueneisen parameter in deep

tissue [55, 132] or in single cells [140]. PAT is capable of measuring overtone vibrational

absorption in the near-infrared spectral region, which can reveal the tissue composition, such

as lipids [141]. Similarly, PAT can be combined with stimulated Raman excitation for

enhanced chemical specificity [142]. In addition, PAT has been used for imaging Förster

resonance energy transfer (FRET), the efficiency of which reflects intra- and inter-molecular

distances in the 1 to 10 nm range [143, 144]. PAT can measure the nonradiative absorption

relaxation time of molecules by fitting the saturation curve of the signal amplitude as a

function of incident laser intensity [145, 146]. Two other material parameters, dichroism

[147] and magnetomotion [8, 148], can be used by PAT to enhance imaging specificity. In

addition to absorber properties, PAT can also measure the microenvironment’s properties,

including pH and partial oxygen pressure (pO2), by using appropriate contrast agents [149–

152].

4.4. Molecular PAT

Endogenous PA contrasts, such as hemoglobin in red blood cells, melanin in melanoma

cells, DNA/RNA in cell nuclei, water in brain edema, and lipids in myelin, are abundant and

nontoxic. However, they may lack the requisite specificity for diagnosing disease or tracking

biological processes. By using exogenous contrasts, molecular PAT enables visualizing

specific cellular functions and molecular processes. In recent years, great efforts have been

devoted to enhance the molecular imaging capability of PAT, and considerable progress has

been made in optimizing both the PAT imaging systems for better detection sensitivity, and

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the contrast agents for better contrast enhancement [153–155]. PAT has proven capable of

high sensitivity molecular imaging by using various exogenous contrast agents, including

microbubbles, organic dyes, nanoparticles, fluorescent proteins, and reporter gene products

[156]. For example, one of the very first demonstrations of molecular PAT was to use

IRDye800-c(KRGDf) to target overexpressed integrin αvβ3 in brain glioblastoma (Figure

9a) [23]. Because of their dramatically different optical absorbing properties, the reported

PA detection sensitivity for exogenous contrast agents varies from millimolar to picomolar

[85, 157].

Compared with organic dyes, nanoparticles can be easily engineered for PA molecular

imaging by tuning their size, shape, and composition for the optimum peak absorption

wavelength [155]. Numerous nanoparticles have been used for PA molecular imaging,

especially in cancer detection [159] and sentinel lymph node mapping [157]. For example,

Kircher et al. have recently developed a brain tumor molecular imaging method using triple-

modality MRI-photoacoustic- Raman nanoparticles (Figure 9b) [158]. A high detection

sensitivity of 50 pM was achieved with an incident laser energy of only 8 mJ/cm2.

PAT of reporter gene products has also attracted more and more attention. A significant

advantage of reporter gene products is that they are expressed in living cells and do not need

complex exogenous delivery. So far, various fluorescent genetically encoded proteins have

been explored for PA molecular imaging, such as mCherry, EGFP, iRFP, and RFP [12, 160–

162]. Nonfluorescent gene products can also be imaged by PAT. For example, given the

strong optical absorption of melanin, tyrosinase genes were transferred to non-melanogenic

cells to encode eumelanin as the contrast agent for PA imaging [52, 54, 163, 164].

5. CONCLUSION

Over the last decade, the PAT technique has been evolving rapidly toward higher spatial

resolution, higher frame rates, and higher detection sensitivity. The applications of PAT

have also expanded greatly in fundamental life sciences, and many clinical applications have

been proposed. The accelerating progress in PAT has also triggered growing contributions

from biology, chemistry, and nanotechnology. With the commercialization of several PAT

systems, we expect that PAT will become a mainstream imaging modality in the lab and

clinic.

While exciting images have been acquired, PAT still faces limitations. For instance, the light

attenuation limits the ultimate imaging depth. Currently, the maximum demonstrated PAT

imaging depth is 8.4 cm in chicken breast tissue [39]. To address this limitation, novel light

illumination schemes have been explored. For instance, by illuminating the object from both

sides [41, 78], the imaging region can be doubled and potentially reach 16.4 cm. Internal

light delivery has also been proposed to image organs far beneath the skin [165]. In terms of

imaging speed, both PACT and PAM are currently limited by the pulse repetition rate of

lasers. With advances in laser technology, we expect the PAT imaging speed to be improved

accordingly. Quantitative PA imaging also faces challenges because of the difficulty in

measuring local fluence distribution. Advanced spectral separation algorithms have been

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proposed to address this issue [116, 117, 166]. Novel contrast agents have also been

explored to improve the specificity of deep-tissue molecular photoacoustic imaging [8, 10].

Nevertheless, exciting PAT images have already been reported, and addressing the

aforementioned challenges will only further improve the capability of PAT. With its unique

combination of optical absorption contrast and ultrasonic imaging depth and resolution

scalability [9], PAT is expected to find more high-impact applications in both biomedical

research and clinical practice.

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tumor molecular imaging strategy using a new triple-modality MRI-photoacoustic-Raman nanoparticle. Nature Medicine. 2012 May.18:829–U235.

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Figure 1. Absorption coefficient spectra of endogenous tissue chromophores at their typical

concentrations in the human body. Oxy-hemoglobin (HbO2) and deoxy-hemoglobin (HbR),

150 gL−1. Water, 60% by weight. Lipid, 16% by weight. Melanin concentration corresponds

to that in normal skin. Adapted from http://omlc.ogi.edu.

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http://omlc.ogi.edu

Figure 2. (a) Schematic illustrating the operation of the Fabry-Perot interferometer-based PACT

imaging system. Photoacoustic waves are generated by the absorption of nanosecond optical

pulses provided by a wavelength-tunable OPO laser and detected by a transparent Fabry-

Perot polymer film ultrasound sensor. The sensor comprises a pair of dichroic mirrors

separated by a 40 µm thick polymer spacer, thus forming a Fabry-Perot interferometer (FPI).

The waves are mapped in 2D by raster-scanning a CW focused interrogation laser beam

across the sensor and recording the acoustically induced modulation of the reflectivity of the

FPI at each scanning point. (b) Maximum amplitude projection of the complete three

dimensional image dataset (depth 0 to 6 mm), showing two embryos (shaded red).

Reproduced with permission from [75].

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Figure 3. (a) Schematic of a ring-shaped confocal photoacoustic computed tomography (RC-PACT)

system. (b)–(c) In vivo RC-PACT images of athymic mice acquired noninvasively at the (b)

liver and (c) kidney regions. BM, backbone muscle; GI, GI tract; KN, kidney; LV, liver; PV,

portal vein; SC, spinal cord; SP, spleen; and VC, vena cava. Reproduced with permission

from [78, 79].

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Figure 4. (a) Photograph of an arc-array-based spherical-view PACT system. (b) Three-dimensional

photoacoustic image of a female nude mouse. Reproduced with permission from [80].

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Figure 5. Photoacoustic microscopy (PAM). (a) Second-generation optical-resolution photoacoustic

microscopy system (2G-OR-PAM), where the lateral resolution is determined by the

diffraction-limited optical focusing. AL, acoustic lens; Corl, correction lens; RAP, right

angled prism; RhP, rhomboid prism; SOL, silicone oil layer; UT, ultrasonic transducer; WT,

water tank. (b) Dark-field acoustic-resolution photoacoustic microscopy (AR-PAM), where

the lateral resolution is determined by the diffraction-limited acoustic focusing. (c–d) In vivo

label-free mouse ear vasculature imaged by (a) OR-PAM and (b) AR-PAM. A

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representative cross-sectional image is shown at the bottom. While OR-PAM shows better

resolution, AR-PAM has greater penetration depth (shown by arrows). Reproduced with

permission from [94].

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Figure 6. Multi-scale photoacoustic images of LacZ gene expression. (a) B-scan image of a lacZ-

marked tumor at a 5-cm depth in biological tissue, acquired by overlaying chicken breast

tissue on top of a mouse. Photoacoustic images are colored green, while ultrasonic images

are in gray. (b) 3D depiction of a composite photoacoustic image, showing the tumor and

blood vessels imaged with AR-PAM. Green: tumor. The scale bar represents 2 mm. (c) An

OR-PAM image of fixed lacZ cells grown on a cover glass after staining with Xgal. nu: cell

nucleus. The scale bar represents 10 µm. Reproduced with permission from [99].

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Figure 7. Super-resolution photoacoustic microscopy. (a) Photoimprint photoacoustic microscopy (PI-

PAM) [102]. Since the photobleaching rate depends on the local excitation intensity, the first

excitation bleaches the center part of the illuminated region more than the periphery, leaving

an imprint in the sample. The differential signal between before- and after-bleaching images

results in a smaller effective excitation size and thus a resolution enhancement, as shown by

the dashed circle in the bottom panel. (b) PI-PAM imaging of gold nanoparticles with

enhanced lateral resolution. (c) Wavefront-shaping assisted sub-acoustic resolution PA

imaging. Each photoacoustic emission from the speckle grains is weighted by the Gaussian

detection sensitivity of the acoustic transducer [104]. (d–e) Photoacoustic images of a sweet

bee wing created with (d) random optical speckle illumination and (e) wavefront optimized

speckle focus, showing the superior resolution of the latter method. Adapted with

permission from [102, 104].

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Figure 8. Multi-parameter PA imaging. (a) Photograph of a mouse ear bearing a U87 glioblastoma

tumor. (b) Depth-encoded vascular image acquired with OR-PAM, showing the tortuous

blood vessels in the tumor. (c) sO2 map of the tumor region, showing the hyperoxic status of

the early-stage tumor.

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Figure 9. Photoacoustic molecular imaging. (a) PACT of a glioblastoma in a mouse brain enhanced by

IRDye800-c(KRGDf), which targeted overexpressed integrin αvβ3 in tumor cells. (b) PAT

of a glioblastoma in a mouse brain enhanced by tri-modality MRI-PA-Raman (MPR)

nanoparticles. Reproduced with permission from [23, 158].

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